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The lack of equal globally binding GHG's emission reduction targets is currently leading to a set of diverging GHG's emission prices across the world (or even no price for GHG's emission in some regions). This may result in distortions with direct implications on competitiveness of the industries in regions with strict climate policies (as the European Union) and can cause the issue of carbon leakage. Carbon leakage is defined as 'the increase in emission outside a region as a direct result of the policy to cap emission in this region'. This paper is the first part of the set of two analysis aiming at the carbon leakage assessment. In the following paper (aimed to be published this year), we will assess the impact of free allowances for emission intensive trade exposed industries (EITE) and the NDCs in the rest of the world countries - for the sake of brevity, we decided to remove these results from the current paper, but they will be presented later this year. The purpose of this paper is to assess the possible scale of the carbon leakage using different assumptions and policy scenarios and identify channels to efficiently prevent the carbon leakage phenomenon. The analysis has been carried out using the computable general equilibrium d-PLACE model developed within the Centre for Climate and Policy Analysis (CAKE).2 Our model is a recursive dynamic multi-regional and multi-commodity tool in which emissions are modelled in great detail, for example, the process and each fossil fuel combustion related emission are modelled separately. Furthermore, the big advantage of the applied model is a very detailed modelling of EU ETS as well as non-ETS emission targets. In the paper, the simulations using two versions of model was presented - with and without endogenous technical change to elaborate on how the assumptions on technical change affect the modelling results and consequent scale of the carbon leakage. Moreover, this paper aims mainly at the assessment of different channels of carbon leakage; therefore, we do not take into account either NDCs in the rest of the world or free allowances for emission intensive trade exposed sectors. These problems will be handled in the next paper, aimed to be published later this year. Using the above mentioned CGE (computable general equilibrium model, we captured the main factors, that determine the carbon leakage rates. We assessed the contribution of three channels - demand channel, competitiveness channel and carbon intensity channel to the risk of carbon leakage. It turned out that carbon intensity channel and competitiveness channel are the most important, while demand channel contributes to changes in GHG's emission only in the most restrictive scenario. Moreover, energy channel was further decomposed to the impact of sectoral structure and influence in emission intensity within each sector - the impact of these two channels is also similar, but dependent on the analysed scenario. Such a decomposition allowed us to determine the main channels through which the carbon leakage occur and pursue relevant policy recommendations. [ABSTRACT FROM AUTHOR]

The atmospheric concentration of CO2 is steadily increasing and causing climate change. To achieve the Paris 1.5 or 2°C target, negative emission technologies must be deployed in addition to reducing carbon emissions. The ocean is a large carbon sink but the potential of marine primary producers to contribute to carbon neutrality remains unclear.Here we review the alterations to carbon capture and sequestration of marine primary producers (including traditional 'blue carbon' plants, microalgae and macroalgae) in the Anthropocene, and, for the first time, assess and compare the potential of various marine primary producers to carbon neutrality and climate change mitigation via biogeoengineering approaches.The contributions of marine primary producers to carbon sequestration have been decreasing in the Anthropocene due to the decrease in biomass driven by direct anthropogenic activities and climate change. The potential of blue carbon plants (mangroves, saltmarshes and seagrasses) is limited by the available areas for their revegetation. Microalgae appear to have a large potential due to their ubiquity but how to enhance their carbon sequestration efficiency is very complex and uncertain. On the other hand, macroalgae can play an essential role in mitigating climate change through extensive offshore cultivation due to higher carbon sequestration capacity and substantial available areas. This approach seems both technically and economically feasible due to the development of offshore aquaculture and a well‐established market for macroalgal products.Synthesis and applications. This paper provides new insights and suggests promising directions for utilizing marine primary producers to achieve the Paris temperature target. We propose that macroalgae cultivation can play an essential role in attaining carbon neutrality and climate change mitigation, although its ecological impacts need to be assessed further. [ABSTRACT FROM AUTHOR]

Emission inventories (EIs) are the fundamental tool to monitor compliance with greenhouse gas (GHG) emissions and emission reduction commitments. Inventory accounting guidelines provide the best practices to help EI compilers across different countries and regions make comparable, national emission estimates regardless of differences in data availability. However, there are a variety of sources of error and uncertainty that originate beyond what the inventory guidelines can define. Spatially explicit EIs, which are a key product for atmospheric modeling applications, are often developed for research purposes and there are no specific guidelines to achieve spatial emission estimates. The errors and uncertainties associated with the spatial estimates are unique to the approaches employed and are often difficult to assess. This study compares the global, high-resolution (1 km), fossil fuel, carbon dioxide (CO2), gridded EI Open-source Data Inventory for Anthropogenic CO2 (ODIAC) with the multi-resolution, spatially explicit bottom-up EI geoinformation technologies, spatio-temporal approaches, and full carbon account for improving the accuracy of GHG inventories (GESAPU) over the domain of Poland. By taking full advantage of the data granularity that bottom-up EI offers, this study characterized the potential biases in spatial disaggregation by emission sector (point and non-point emissions) across different scales (national, subnational/regional, and urban policy-relevant scales) and identified the root causes. While two EIs are in agreement in total and sectoral emissions (2.2% for the total emissions), the emission spatial patterns showed large differences (10~100% relative differences at 1 km) especially at the urban-rural transitioning areas (90–100%). We however found that the agreement of emissions over urban areas is surprisingly good compared with the estimates previously reported for US cities. This paper also discusses the use of spatially explicit EIs for climate mitigation applications beyond the common use in atmospheric modeling. We conclude with a discussion of current and future challenges of EIs in support of successful implementation of GHG emission monitoring and mitigation activity under the Paris Climate Agreement from the United Nations Framework Convention on Climate Change (UNFCCC) 21st Conference of the Parties (COP21). We highlight the importance of capacity building for EI development and coordinated research efforts of EI, atmospheric observations, and modeling to overcome the challenges. [ABSTRACT FROM AUTHOR]

Monitoring the implementation of emission commitments under the Paris agreement relies on accurate estimates of terrestrial carbon fluxes. Here, we assimilate a 21st century observation-based time series of woody vegetation carbon densities into a bookkeeping model (BKM). This approach allows us to disentangle the observation-based carbon fluxes by terrestrial woody vegetation into anthropogenic and environmental contributions. Estimated emissions (from land-use and land cover changes) between 2000 and 2019 amount to 1.4 PgC yr−1, reducing the difference to other carbon cycle model estimates by up to 88% compared to previous estimates with the BKM (without the data assimilation). Our estimates suggest that the global woody vegetation carbon sink due to environmental processes (1.5 PgC yr−1) is weaker and more susceptible to interannual variations and extreme events than estimated by state-of-the-art process-based carbon cycle models. These findings highlight the need to advance model-data integration to improve estimates of the terrestrial carbon cycle under the Global Stocktake. Accurate estimates of carbon fluxes are important to our understanding of the carbon cycle. Here, via model-data integration, the authors disentangle anthropogenic and environmental carbon flux contributions of terrestrial woody vegetation, and find that environmental processes are weaker and more susceptible to interannual variations and extreme events in the 21st century than previously estimated. [ABSTRACT FROM AUTHOR]

Scenarios avoiding global warming greater than 1.5 or 2 ∘ C, as stipulated in the Paris Agreement, may require the combined mitigation of anthropogenic greenhouse gas emissions alongside enhancing negative emissions through approaches such as afforestation–reforestation (AR) and biomass energy with carbon capture and storage (BECCS). We use the JULES land surface model coupled to an inverted form of the IMOGEN climate emulator to investigate mitigation scenarios that achieve the 1.5 or 2 ∘ C warming targets of the Paris Agreement. Specifically, within this IMOGEN-JULES framework, we focus on and characterise the global and regional effectiveness of land-based (BECCS and/or AR) and anthropogenic methane (CH4) emission mitigation, separately and in combination, on the anthropogenic fossil fuel carbon dioxide (CO2) emission budgets (AFFEBs) to 2100. We use consistent data and socio-economic assumptions from the IMAGE integrated assessment model for the second Shared Socioeconomic Pathway (SSP2). The analysis includes the effects of the methane and carbon–climate feedbacks from wetlands and permafrost thaw, which we have shown previously to be significant constraints on the AFFEBs. Globally, mitigation of anthropogenic CH4 emissions has large impacts on the anthropogenic fossil fuel emission budgets, potentially offsetting (i.e. allowing extra) carbon dioxide emissions of 188–212 Gt C. This is because of (a) the reduction in the direct and indirect radiative forcing of methane in response to the lower emissions and hence atmospheric concentration of methane and (b) carbon-cycle changes leading to increased uptake by the land and ocean by CO2 -based fertilisation. Methane mitigation is beneficial everywhere, particularly for the major CH4 -emitting regions of India, the USA, and China. Land-based mitigation has the potential to offset 51–100 Gt C globally, the large range reflecting assumptions and uncertainties associated with BECCS. The ranges for CH4 reduction and BECCS implementation are valid for both the 1.5 and 2 ∘ C warming targets. That is the mitigation potential of the CH4 and of the land-based scenarios is similar for regardless of which of the final stabilised warming levels society aims for. Further, both the effectiveness and the preferred land management strategy (i.e. AR or BECCS) have strong regional dependencies. Additional analysis shows extensive BECCS could adversely affect water security for several regions. Although the primary requirement remains mitigation of fossil fuel emissions, our results highlight the potential for the mitigation of CH4 emissions to make the Paris climate targets more achievable. [ABSTRACT FROM AUTHOR]

Biomass-based negative emission technologies (NETs) such as bioenergy with carbon capture and storage (BECCS) and afforestation/reforestation (AR) are regarded as important options to achieve the 2 °C and 1.5 °C targets stipulated in the Paris agreement, but the feasibility of their large-scale deployments remains very uncertain. This study focused on the speed of expansions of land-use area related to the biomass-based NETs and assessed the feasibility of climate change mitigation scenarios to achieve the temperature targets. Our model analysis shows that expansions at unprecedented speeds are required for total cropland area (including energy cropland) in Sub-Saharan Africa and for planted forest area for carbon sink in many regions in the next decades, under the assumption of global least-cost measures for CO2 emission reduction. On the other hand, when the speed of the land-use expansions is limited as observed in the real world, the CO2 emission reduction costs become unrealistically high around the middle of this century, particularly in scenarios for the 1.5 °C target; relatively low-cost measures such as BECCS in Sub-Saharan Africa and AR in many regions are limited in deployment due to the limited speed of the land-use expansion, and yet energy systems must be transformed to nearly net-zero/negative CO2 emissions for the 2 °C/1.5 °C target, which necessitates using other mitigation technologies of much higher costs. These results may cause concern over the feasibility of achieving the temperature targets, especially for the 1.5 °C target, and point to technical and scenario design aspects that will need further research for biomass-based NETs and their allowable expansion speed. [ABSTRACT FROM AUTHOR]

The Greenhouse gas Laser Imaging Tomography Experiment (GreenLITE™) trace gas measurement system, jointly designed and developed by Atmospheric and Environmental Research, Inc. and Spectral Sensor Solutions LLC, provides high-precision, long-path measurements of atmospheric trace gases including CO2 and CH4 over extended (0.04–25 km 2) areas of interest. In 2015, a prototype unit was deployed in Paris, France, to demonstrate its ability to provide continuous observations of CO2 concentrations along horizontal air segments and two-dimensional (2-D) maps of time-varying CO2 concentrations over a complex urban environment. Subsequently, these data have been adapted to create a physically consistent set of horizontal segment mean concentrations for (1) comparisons to highly accurate in situ point measurements obtained for coincident times within the Greater Paris area, (2) inter-comparisons with results from high spatial and temporal regional carbon cycle model data, and (3) potential assimilation of these data to constrain and inform regional carbon cycle modeling frameworks. To achieve these ends, the GreenLITE™ data are calibrated against precise in situ point measurements to reconcile constant systematic as well as slowly varying temporal differences that exist between in situ and GreenLITE™ measurements to provide unbiased comparisons, and the potential for long-term co-assimilation of both measurements into urban-scale emission models. While both the constant systematic biases and the slowly varying differences may have different impacts on the measurement accuracy and/or precisions, they are in part due to a number of potential common terms that include limitation in the instrument design, uncertainties in spectroscopy and imprecise knowledge of the atmospheric state. This work provides a brief overview of the system design and the current gas concentration retrieval and 2-D reconstruction approaches, a description of the bias-correction approach, the results as applied to data collected in Paris, France, and an analysis of the inter-comparison between collocated in situ measurements and GreenLITE™ observations. [ABSTRACT FROM AUTHOR]